1. Field of the Invention
The present invention relates to a denoising method and apparatus for performing the process of inhibiting noise components on a digital image acquired by imaging a subject to enhance the picture quality, and to a program for carrying out that method.
2. Description of the Related Art
Processes for the purpose of inhibiting or eliminating noise from a photographic image containing a person's face (hereinafter referred to simply as an image) have hitherto been performed. For example, low-pass filters that are usually used for eliminating noise can be applied. However, while low-pass filters can inhibit noise components from an image, they will degrade an edge portion contained in an image signal and blur the entire image.
An ε-filter (ε-separation nonlinear digital filter), which is designed to separate and inhibit a high-frequency noise component of low amplitude contained in an image by generating use of the fact that many of the noise components exist as signals of low amplitude in the high-frequency component of an image, is also applied to eliminate noise (H. Kondo et al., “Colored Face Image Processing by Vector ε-Filter-Removal of Wrinkles -”, Drafts in the National Meeting of the Academic Society for Electronic Information Communication, D-11-143, p. 143, 1998). Since the ε-filter has the property of flattening only a change in the level of low amplitude contained in an image signal, an image processed by the ε-filter preserves edges having a sharp change in the level of the amplitude and hardly loses the entire sharpness.
The ε-filter is basically constructed to subtract from an original image signal a value obtained by applying a nonlinear function to a change of quantity in the level of the amplitude of the signal. This nonlinear function outputs a value of 0 when the amplitude of a signal is greater than a predetermined threshold value (ε0). That is, when the ε-filter is employed, the output of the nonlinear function is 0 at a part in an image that has an amplitude greater than the aforementioned threshold value. In a processed image, the original signal of apart having an amplitude greater than the aforementioned threshold value is preserved. On the other hand, in a part whose amplitude is the aforementioned threshold value or less, the signal value of that processed part is a value obtained by subtracting the output of the nonlinear function (where the absolute value is greater than 0) from the original signal value. In this manner, the change in light and shade is smoothed. As a result, edges whose amplitude is high can be preserved while generating noise indistinct.
A variety of techniques have been proposed for extracting signals of different frequency bands from an image. For instance, U.S. Pat. No. 5,991,457 discloses a method for generating a plurality of blurredly masked images different in frequency response characteristics from one another, based on an original image and also generating a plurality of band-limited images respectively representing signals of different frequency bands of the original image, based on the original image and blurredly masked images, or based on the blurredly masked images. U.S. Pat. No. 5,991,457 discloses a method for efficiently generating a blurredly masked image by reducing the amount of calculation required in generating the blurredly masked image.
However, many of the noise components exist in high-frequency bands, but they exist over the entire range from high-frequency bands to low-frequency bands. The aforementioned process method utilizing the ε-filter cannot completely eliminate noise components, because it extracts the noise components only in a single frequency band and subtracts the extracted components from the original image. In the aforementioned method for extracting noise components at a single frequency band, if the effect of eliminating noise are to be improved, filtering must be enhanced at the single frequency band, that is, the aforementioned threshold value (ε0) for extracting noise must be increased. However, this can easily introduce artifacts into a processed image and debase the picture quality.